Overview

Dataset statistics

Number of variables12
Number of observations319208
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.2 MiB
Average record size in memory96.0 B

Variable types

Numeric12

Alerts

df_index is highly correlated with IDHigh correlation
ID is highly correlated with df_indexHigh correlation
u is highly correlated with g and 6 other fieldsHigh correlation
g is highly correlated with u and 7 other fieldsHigh correlation
r is highly correlated with u and 7 other fieldsHigh correlation
i is highly correlated with u and 7 other fieldsHigh correlation
z is highly correlated with u and 7 other fieldsHigh correlation
uErr is highly correlated with u and 7 other fieldsHigh correlation
gErr is highly correlated with u and 8 other fieldsHigh correlation
rErr is highly correlated with u and 8 other fieldsHigh correlation
iErr is highly correlated with g and 7 other fieldsHigh correlation
zErr is highly correlated with gErr and 2 other fieldsHigh correlation
df_index is highly correlated with IDHigh correlation
ID is highly correlated with df_indexHigh correlation
u is highly correlated with g and 5 other fieldsHigh correlation
g is highly correlated with u and 5 other fieldsHigh correlation
r is highly correlated with u and 5 other fieldsHigh correlation
i is highly correlated with u and 5 other fieldsHigh correlation
z is highly correlated with u and 5 other fieldsHigh correlation
uErr is highly correlated with u and 5 other fieldsHigh correlation
gErr is highly correlated with u and 6 other fieldsHigh correlation
rErr is highly correlated with gErr and 1 other fieldsHigh correlation
iErr is highly correlated with rErrHigh correlation
df_index is highly correlated with IDHigh correlation
ID is highly correlated with df_indexHigh correlation
u is highly correlated with g and 5 other fieldsHigh correlation
g is highly correlated with u and 6 other fieldsHigh correlation
r is highly correlated with u and 6 other fieldsHigh correlation
i is highly correlated with u and 6 other fieldsHigh correlation
z is highly correlated with u and 6 other fieldsHigh correlation
uErr is highly correlated with u and 6 other fieldsHigh correlation
gErr is highly correlated with u and 7 other fieldsHigh correlation
rErr is highly correlated with g and 7 other fieldsHigh correlation
iErr is highly correlated with gErr and 2 other fieldsHigh correlation
zErr is highly correlated with rErr and 1 other fieldsHigh correlation
df_index is highly correlated with IDHigh correlation
ID is highly correlated with df_indexHigh correlation
u is highly correlated with g and 4 other fieldsHigh correlation
g is highly correlated with u and 6 other fieldsHigh correlation
r is highly correlated with u and 6 other fieldsHigh correlation
i is highly correlated with u and 5 other fieldsHigh correlation
z is highly correlated with u and 3 other fieldsHigh correlation
uErr is highly correlated with uHigh correlation
gErr is highly correlated with g and 3 other fieldsHigh correlation
rErr is highly correlated with g and 4 other fieldsHigh correlation
iErr is highly correlated with g and 5 other fieldsHigh correlation
zErr is highly correlated with iErrHigh correlation
rErr is highly skewed (γ1 = 54.93743197) Skewed
iErr is highly skewed (γ1 = 90.19458746) Skewed
zErr is highly skewed (γ1 = 172.4633831) Skewed
ID has unique values Unique
uErr has unique values Unique
gErr has unique values Unique
rErr has unique values Unique
iErr has unique values Unique
zErr has unique values Unique

Reproduction

Analysis started2022-02-24 03:28:50.843873
Analysis finished2022-02-24 03:29:29.683399
Duration38.84 seconds
Software versionpandas-profiling v3.1.1
Download configurationconfig.json

Variables

df_index
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct97980
Distinct (%)30.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40979.24784
Minimum0
Maximum97979
Zeros4
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2022-02-24T00:29:29.737672image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4033
Q120168
median40346
Q360531.25
95-th percentile82018.65
Maximum97979
Range97979
Interquartile range (IQR)40363.25

Descriptive statistics

Standard deviation24455.83284
Coefficient of variation (CV)0.5967857911
Kurtosis-0.9120990318
Mean40979.24784
Median Absolute Deviation (MAD)20182
Skewness0.1773169409
Sum1.308090374 × 1010
Variance598087760
MonotonicityNot monotonic
2022-02-24T00:29:29.821847image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
04
 
< 0.1%
488594
 
< 0.1%
488654
 
< 0.1%
488644
 
< 0.1%
488634
 
< 0.1%
488624
 
< 0.1%
488614
 
< 0.1%
488604
 
< 0.1%
488574
 
< 0.1%
488674
 
< 0.1%
Other values (97970)319168
> 99.9%
ValueCountFrequency (%)
04
< 0.1%
14
< 0.1%
24
< 0.1%
34
< 0.1%
43
< 0.1%
54
< 0.1%
64
< 0.1%
74
< 0.1%
84
< 0.1%
94
< 0.1%
ValueCountFrequency (%)
979791
< 0.1%
979781
< 0.1%
979771
< 0.1%
979761
< 0.1%
979751
< 0.1%
979741
< 0.1%
979731
< 0.1%
979721
< 0.1%
979711
< 0.1%
979701
< 0.1%

ID
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct319208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.237664596 × 1018
Minimum1.23764588 × 1018
Maximum1.237680531 × 1018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2022-02-24T00:29:29.915598image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum1.23764588 × 1018
5-th percentile1.237651497 × 1018
Q11.237658492 × 1018
median1.237663783 × 1018
Q31.237668298 × 1018
95-th percentile1.237679543 × 1018
Maximum1.237680531 × 1018
Range3.465177858 × 1013
Interquartile range (IQR)9.805951091 × 1012

Descriptive statistics

Standard deviation8.395202021 × 1012
Coefficient of variation (CV)6.783099434 × 10-6
Kurtosis-0.5679826921
Mean1.237664596 × 1018
Median Absolute Deviation (MAD)4.713716777 × 1012
Skewness0.3631085514
Sum-1.477475714 × 1018
Variance7.047941697 × 1025
MonotonicityNot monotonic
2022-02-24T00:29:30.071848image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.237645943 × 10181
 
< 0.1%
1.237667211 × 10181
 
< 0.1%
1.237667211 × 10181
 
< 0.1%
1.237667211 × 10181
 
< 0.1%
1.237667211 × 10181
 
< 0.1%
1.237667211 × 10181
 
< 0.1%
1.237667211 × 10181
 
< 0.1%
1.237667211 × 10181
 
< 0.1%
1.237667211 × 10181
 
< 0.1%
1.237667211 × 10181
 
< 0.1%
Other values (319198)319198
> 99.9%
ValueCountFrequency (%)
1.23764588 × 10181
< 0.1%
1.237645943 × 10181
< 0.1%
1.237645943 × 10181
< 0.1%
1.237645943 × 10181
< 0.1%
1.237645943 × 10181
< 0.1%
1.237645943 × 10181
< 0.1%
1.237645943 × 10181
< 0.1%
1.237645943 × 10181
< 0.1%
1.237645943 × 10181
< 0.1%
1.237645943 × 10181
< 0.1%
ValueCountFrequency (%)
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%
1.237680531 × 10181
< 0.1%

u
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct298932
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.95571241
Minimum11.754014
Maximum30.553564
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2022-02-24T00:29:30.174033image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum11.754014
5-th percentile19.58619625
Q121.0533355
median22.0237545
Q322.7759675
95-th percentile24.3148458
Maximum30.553564
Range18.79955
Interquartile range (IQR)1.722632

Descriptive statistics

Standard deviation1.441545897
Coefficient of variation (CV)0.06565698574
Kurtosis1.300361176
Mean21.95571241
Median Absolute Deviation (MAD)0.8494615
Skewness0.0171208624
Sum7008439.047
Variance2.078054572
MonotonicityNot monotonic
2022-02-24T00:29:30.267770image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21.8332395
 
< 0.1%
21.8129655
 
< 0.1%
22.2653585
 
< 0.1%
20.6144714
 
< 0.1%
22.1097014
 
< 0.1%
22.7508344
 
< 0.1%
22.0462784
 
< 0.1%
20.8185394
 
< 0.1%
22.1234114
 
< 0.1%
22.4155714
 
< 0.1%
Other values (298922)319165
> 99.9%
ValueCountFrequency (%)
11.7540141
< 0.1%
12.3453271
< 0.1%
12.4588811
< 0.1%
13.2300871
< 0.1%
13.3569751
< 0.1%
13.5879131
< 0.1%
13.8825591
< 0.1%
13.9461341
< 0.1%
13.9848251
< 0.1%
14.0933311
< 0.1%
ValueCountFrequency (%)
30.5535641
< 0.1%
28.8272191
< 0.1%
28.8091771
< 0.1%
28.1116261
< 0.1%
27.9109551
< 0.1%
27.9089261
< 0.1%
27.7614361
< 0.1%
27.7462221
< 0.1%
27.7332861
< 0.1%
27.7127881
< 0.1%

g
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct299157
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.1937704
Minimum11.576696
Maximum30.612074
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2022-02-24T00:29:30.361532image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum11.576696
5-th percentile17.95138795
Q119.1950795
median20.3703585
Q321.16579325
95-th percentile22.1656982
Maximum30.612074
Range19.035378
Interquartile range (IQR)1.97071375

Descriptive statistics

Standard deviation1.350955053
Coefficient of variation (CV)0.06689959459
Kurtosis0.2018201373
Mean20.1937704
Median Absolute Deviation (MAD)0.9432195
Skewness-0.3866214376
Sum6446013.063
Variance1.825079556
MonotonicityNot monotonic
2022-02-24T00:29:30.439657image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21.6402875
 
< 0.1%
21.5501085
 
< 0.1%
18.9039425
 
< 0.1%
20.5759984
 
< 0.1%
20.2238184
 
< 0.1%
21.182484
 
< 0.1%
20.8321154
 
< 0.1%
19.772234
 
< 0.1%
20.7723464
 
< 0.1%
20.7381974
 
< 0.1%
Other values (299147)319165
> 99.9%
ValueCountFrequency (%)
11.5766961
< 0.1%
12.1299261
< 0.1%
12.276731
< 0.1%
12.5514651
< 0.1%
12.7043431
< 0.1%
12.9121421
< 0.1%
12.9225141
< 0.1%
12.9534351
< 0.1%
13.0144811
< 0.1%
13.0340891
< 0.1%
ValueCountFrequency (%)
30.6120741
< 0.1%
29.7172151
< 0.1%
27.4978581
< 0.1%
26.7244171
< 0.1%
26.6321871
< 0.1%
26.3971141
< 0.1%
26.1213511
< 0.1%
25.9690741
< 0.1%
25.8737431
< 0.1%
25.7411231
< 0.1%

r
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct296257
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.69537737
Minimum11.48799
Maximum29.998732
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2022-02-24T00:29:30.549033image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum11.48799
5-th percentile16.94530785
Q117.8054985
median18.713879
Q319.44761225
95-th percentile20.585991
Maximum29.998732
Range18.510742
Interquartile range (IQR)1.64211375

Descriptive statistics

Standard deviation1.160189529
Coefficient of variation (CV)0.06205756136
Kurtosis0.1339707822
Mean18.69537737
Median Absolute Deviation (MAD)0.81902
Skewness-0.07176924683
Sum5967714.02
Variance1.346039742
MonotonicityNot monotonic
2022-02-24T00:29:30.640808image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18.7311125
 
< 0.1%
19.1755854
 
< 0.1%
18.6091584
 
< 0.1%
19.1153034
 
< 0.1%
19.1549614
 
< 0.1%
18.9512624
 
< 0.1%
18.7582554
 
< 0.1%
17.9956554
 
< 0.1%
17.5619184
 
< 0.1%
19.2778684
 
< 0.1%
Other values (296247)319167
> 99.9%
ValueCountFrequency (%)
11.487991
< 0.1%
11.5504751
< 0.1%
11.6575461
< 0.1%
11.7623351
< 0.1%
11.8844851
< 0.1%
11.9465471
< 0.1%
12.0181591
< 0.1%
12.223331
< 0.1%
12.2451321
< 0.1%
12.3915641
< 0.1%
ValueCountFrequency (%)
29.9987321
< 0.1%
29.3467521
< 0.1%
27.3994181
< 0.1%
25.8010751
< 0.1%
24.8350891
< 0.1%
24.7557831
< 0.1%
24.7557451
< 0.1%
24.7508451
< 0.1%
24.7499561
< 0.1%
24.7465081
< 0.1%

i
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct293614
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.06930171
Minimum11.023721
Maximum29.780376
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2022-02-24T00:29:30.725195image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum11.023721
5-th percentile16.49034515
Q117.29459775
median18.107736
Q318.7590085
95-th percentile19.6816762
Maximum29.780376
Range18.756655
Interquartile range (IQR)1.46441075

Descriptive statistics

Standard deviation1.028597323
Coefficient of variation (CV)0.05692512854
Kurtosis0.520610338
Mean18.06930171
Median Absolute Deviation (MAD)0.732417
Skewness-0.1574208866
Sum5767865.661
Variance1.058012452
MonotonicityNot monotonic
2022-02-24T00:29:30.818944image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17.6607614
 
< 0.1%
18.5521074
 
< 0.1%
17.3129964
 
< 0.1%
18.7249264
 
< 0.1%
18.6943994
 
< 0.1%
18.5362224
 
< 0.1%
18.2531744
 
< 0.1%
18.3282534
 
< 0.1%
18.181954
 
< 0.1%
16.8901484
 
< 0.1%
Other values (293604)319168
> 99.9%
ValueCountFrequency (%)
11.0237211
< 0.1%
11.1717331
< 0.1%
11.223971
< 0.1%
11.3030941
< 0.1%
11.4867791
< 0.1%
11.8473641
< 0.1%
11.9138561
< 0.1%
11.922771
< 0.1%
11.9959911
< 0.1%
12.0199811
< 0.1%
ValueCountFrequency (%)
29.7803761
< 0.1%
27.967811
< 0.1%
25.7754781
< 0.1%
24.7235091
< 0.1%
24.5913961
< 0.1%
24.4108031
< 0.1%
24.4018841
< 0.1%
24.3399721
< 0.1%
24.3385661
< 0.1%
24.3312341
< 0.1%

z
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct292925
Distinct (%)91.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.70313181
Minimum10.680226
Maximum28.568005
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2022-02-24T00:29:30.912695image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum10.680226
5-th percentile16.1608012
Q116.9609125
median17.735658
Q318.3682895
95-th percentile19.27754315
Maximum28.568005
Range17.887779
Interquartile range (IQR)1.407377

Descriptive statistics

Standard deviation1.005014595
Coefficient of variation (CV)0.05677044071
Kurtosis0.712640595
Mean17.70313181
Median Absolute Deviation (MAD)0.7055785
Skewness-0.1115929196
Sum5650981.3
Variance1.010054336
MonotonicityNot monotonic
2022-02-24T00:29:31.006444image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16.8922825
 
< 0.1%
17.6950364
 
< 0.1%
17.9499664
 
< 0.1%
16.665974
 
< 0.1%
17.9526624
 
< 0.1%
19.1994994
 
< 0.1%
17.850784
 
< 0.1%
17.948874
 
< 0.1%
18.3005144
 
< 0.1%
17.4876174
 
< 0.1%
Other values (292915)319167
> 99.9%
ValueCountFrequency (%)
10.6802261
< 0.1%
10.9023261
< 0.1%
10.9322171
< 0.1%
10.9714771
< 0.1%
11.1482761
< 0.1%
11.520191
< 0.1%
11.5408111
< 0.1%
11.547521
< 0.1%
11.5910191
< 0.1%
11.6875671
< 0.1%
ValueCountFrequency (%)
28.5680051
< 0.1%
27.7373771
< 0.1%
24.6665591
< 0.1%
24.3467181
< 0.1%
24.1179941
< 0.1%
23.6508061
< 0.1%
23.5537091
< 0.1%
23.5397721
< 0.1%
23.5218281
< 0.1%
23.4919871
< 0.1%

uErr
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct319208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4094936765
Minimum0.01319976295
Maximum6.87985948
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2022-02-24T00:29:31.151503image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.01319976295
5-th percentile0.06318262868
Q10.1789683518
median0.3378770764
Q30.5512002404
95-th percentile1.0066717
Maximum6.87985948
Range6.866659717
Interquartile range (IQR)0.3722318886

Descriptive statistics

Standard deviation0.3121141486
Coefficient of variation (CV)0.7621952828
Kurtosis6.787888315
Mean0.4094936765
Median Absolute Deviation (MAD)0.1772724946
Skewness1.781553518
Sum130713.6575
Variance0.09741524173
MonotonicityNot monotonic
2022-02-24T00:29:31.246909image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.31266739771
 
< 0.1%
0.09124503171
 
< 0.1%
0.32995823491
 
< 0.1%
0.2822994371
 
< 0.1%
0.23814500351
 
< 0.1%
0.33098598211
 
< 0.1%
0.096018195351
 
< 0.1%
0.37355948671
 
< 0.1%
0.43982666021
 
< 0.1%
0.078256249641
 
< 0.1%
Other values (319198)319198
> 99.9%
ValueCountFrequency (%)
0.013199762951
< 0.1%
0.013351245231
< 0.1%
0.013734932251
< 0.1%
0.013781115711
< 0.1%
0.014017055791
< 0.1%
0.014196309771
< 0.1%
0.01429924121
< 0.1%
0.014378763161
< 0.1%
0.014417376561
< 0.1%
0.014555045111
< 0.1%
ValueCountFrequency (%)
6.879859481
< 0.1%
6.7429281431
< 0.1%
5.6244795851
< 0.1%
5.0871977181
< 0.1%
4.3853555731
< 0.1%
4.1876095441
< 0.1%
4.1051012171
< 0.1%
4.0095476021
< 0.1%
4.0002616391
< 0.1%
3.950198591
< 0.1%

gErr
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
UNIQUE

Distinct319208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.09055997065
Minimum0.02266076487
Maximum6.429339305
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2022-02-24T00:29:31.340654image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.02266076487
5-th percentile0.03280795075
Q10.04590485922
median0.07179831984
Q30.1095478901
95-th percentile0.2045915797
Maximum6.429339305
Range6.40667854
Interquartile range (IQR)0.06364303084

Descriptive statistics

Standard deviation0.08046237555
Coefficient of variation (CV)0.8884982512
Kurtosis544.4833595
Mean0.09055997065
Median Absolute Deviation (MAD)0.02922428509
Skewness12.58737434
Sum28907.46711
Variance0.00647419388
MonotonicityNot monotonic
2022-02-24T00:29:31.418792image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.053220893961
 
< 0.1%
0.031037950611
 
< 0.1%
0.064299768711
 
< 0.1%
0.070833891331
 
< 0.1%
0.0523954591
 
< 0.1%
0.054246249811
 
< 0.1%
0.02883733131
 
< 0.1%
0.056191170131
 
< 0.1%
0.07008770081
 
< 0.1%
0.032777805671
 
< 0.1%
Other values (319198)319198
> 99.9%
ValueCountFrequency (%)
0.022660764871
< 0.1%
0.022828972741
< 0.1%
0.023102717821
< 0.1%
0.023115472781
< 0.1%
0.023144557781
< 0.1%
0.023233031931
< 0.1%
0.023315237751
< 0.1%
0.023337676521
< 0.1%
0.023396515781
< 0.1%
0.023398536521
< 0.1%
ValueCountFrequency (%)
6.4293393051
< 0.1%
6.2321475771
< 0.1%
5.3016349521
< 0.1%
5.2754343651
< 0.1%
4.7053938451
< 0.1%
4.1264177781
< 0.1%
3.927791421
< 0.1%
3.8854182221
< 0.1%
3.8027312941
< 0.1%
3.7364649551
< 0.1%

rErr
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED
UNIQUE

Distinct319208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.07355135891
Minimum0.03485844218
Maximum7.180163959
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2022-02-24T00:29:31.512542image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.03485844218
5-th percentile0.04587208495
Q10.05383030746
median0.06390395788
Q30.08169309802
95-th percentile0.1341585255
Maximum7.180163959
Range7.145305517
Interquartile range (IQR)0.02786279056

Descriptive statistics

Standard deviation0.04240716313
Coefficient of variation (CV)0.5765653248
Kurtosis7012.291833
Mean0.07355135891
Median Absolute Deviation (MAD)0.01213871963
Skewness54.93743197
Sum23478.18217
Variance0.001798367485
MonotonicityNot monotonic
2022-02-24T00:29:31.606290image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.051426652411
 
< 0.1%
0.048733092591
 
< 0.1%
0.059881023821
 
< 0.1%
0.059699565061
 
< 0.1%
0.06035571511
 
< 0.1%
0.054884180131
 
< 0.1%
0.044438108541
 
< 0.1%
0.053501870521
 
< 0.1%
0.075844525771
 
< 0.1%
0.052719127231
 
< 0.1%
Other values (319198)319198
> 99.9%
ValueCountFrequency (%)
0.034858442181
< 0.1%
0.035353798171
< 0.1%
0.035422473781
< 0.1%
0.035820037441
< 0.1%
0.035876852561
< 0.1%
0.03591975151
< 0.1%
0.03594233931
< 0.1%
0.035980422381
< 0.1%
0.035989162941
< 0.1%
0.036075722361
< 0.1%
ValueCountFrequency (%)
7.1801639591
< 0.1%
6.1650680511
< 0.1%
5.8551214741
< 0.1%
4.7793472441
< 0.1%
4.7638013361
< 0.1%
4.7427474771
< 0.1%
4.1996968841
< 0.1%
4.0542252631
< 0.1%
3.0811559271
< 0.1%
2.7849590561
< 0.1%

iErr
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED
UNIQUE

Distinct319208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.08099668136
Minimum0.03881203054
Maximum8.400347923
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2022-02-24T00:29:31.706386image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.03881203054
5-th percentile0.05671268735
Q10.06526949532
median0.07464581717
Q30.08892923472
95-th percentile0.1234753837
Maximum8.400347923
Range8.361535893
Interquartile range (IQR)0.0236597394

Descriptive statistics

Standard deviation0.04822283188
Coefficient of variation (CV)0.5953679962
Kurtosis12239.40423
Mean0.08099668136
Median Absolute Deviation (MAD)0.0109526043
Skewness90.19458746
Sum25854.78866
Variance0.002325441514
MonotonicityNot monotonic
2022-02-24T00:29:31.779521image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.055731304361
 
< 0.1%
0.067470991471
 
< 0.1%
0.075080663051
 
< 0.1%
0.076012552281
 
< 0.1%
0.079864955581
 
< 0.1%
0.069487343131
 
< 0.1%
0.060215854851
 
< 0.1%
0.067394885781
 
< 0.1%
0.10136291081
 
< 0.1%
0.073556457981
 
< 0.1%
Other values (319198)319198
> 99.9%
ValueCountFrequency (%)
0.038812030541
< 0.1%
0.042700866651
< 0.1%
0.043017095221
< 0.1%
0.043129079441
< 0.1%
0.043481026761
< 0.1%
0.043634862671
< 0.1%
0.043775619511
< 0.1%
0.043859612291
< 0.1%
0.043978068121
< 0.1%
0.043981768051
< 0.1%
ValueCountFrequency (%)
8.4003479231
< 0.1%
8.0382233741
< 0.1%
7.8646871251
< 0.1%
6.489090481
< 0.1%
5.9628996521
< 0.1%
5.9539833471
< 0.1%
5.7991061361
< 0.1%
5.6970220251
< 0.1%
5.4225917771
< 0.1%
4.8295511191
< 0.1%

zErr
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
SKEWED
UNIQUE

Distinct319208
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.11688808
Minimum0.04474935232
Maximum29.87530183
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 MiB
2022-02-24T00:29:31.873271image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum0.04474935232
5-th percentile0.07541476358
Q10.09084386398
median0.1066164109
Q30.1293862815
95-th percentile0.1851948687
Maximum29.87530183
Range29.83055248
Interquartile range (IQR)0.03854241756

Descriptive statistics

Standard deviation0.09020147448
Coefficient of variation (CV)0.7716909584
Kurtosis48261.30785
Mean0.11688808
Median Absolute Deviation (MAD)0.01815410665
Skewness172.4633831
Sum37311.61024
Variance0.008136305998
MonotonicityNot monotonic
2022-02-24T00:29:31.967021image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.075440277061
 
< 0.1%
0.1118771851
 
< 0.1%
0.11393330251
 
< 0.1%
0.11612160661
 
< 0.1%
0.12494028321
 
< 0.1%
0.10145130461
 
< 0.1%
0.091876354681
 
< 0.1%
0.099030032591
 
< 0.1%
0.16254815271
 
< 0.1%
0.12912325251
 
< 0.1%
Other values (319198)319198
> 99.9%
ValueCountFrequency (%)
0.044749352321
< 0.1%
0.045658706181
< 0.1%
0.048938930671
< 0.1%
0.049045324311
< 0.1%
0.049204802861
< 0.1%
0.049237841251
< 0.1%
0.049372547161
< 0.1%
0.049375802161
< 0.1%
0.04939584521
< 0.1%
0.049420440521
< 0.1%
ValueCountFrequency (%)
29.875301831
< 0.1%
20.344445131
< 0.1%
15.399468741
< 0.1%
9.0348090811
< 0.1%
8.5401514621
< 0.1%
4.747864871
< 0.1%
4.1962998581
< 0.1%
3.8071627221
< 0.1%
3.4932460111
< 0.1%
3.4924105461
< 0.1%

Interactions

2022-02-24T00:29:26.815044image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:02.428655image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:04.537001image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:06.827768image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:09.187695image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:11.438560image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:13.686841image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:16.061398image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:18.381551image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:20.589710image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:22.715151image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:24.758734image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:26.983618image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:02.615179image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:04.704535image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:07.015336image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:09.356340image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:11.627692image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:13.895047image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:16.242827image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:18.564540image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:20.759627image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:22.884834image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:24.926204image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:27.150338image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:02.788113image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:04.890868image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:07.211910image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:09.539619image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:11.814637image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:14.103152image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:16.430853image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:18.754333image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:20.933930image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:23.068082image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:25.092854image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:27.332243image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:02.965015image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:05.072948image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:07.414803image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:09.722077image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:11.998019image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:14.374545image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:16.617419image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:18.937505image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:21.105758image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:23.243092image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:25.332826image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:27.501975image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:03.148360image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:05.272287image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:07.613578image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:09.908719image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:12.212855image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:14.568064image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:16.797579image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:19.119500image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:21.280360image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:23.410463image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:25.494481image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:27.668248image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:03.317307image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:05.475690image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:07.815846image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:10.090335image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:12.414241image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:14.756158image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:16.981692image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:19.289904image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:21.455914image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:23.590626image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:25.662405image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:27.897765image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:03.500681image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:05.731012image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:08.005499image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:10.275069image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:12.599283image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:14.957361image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:17.240693image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:19.469619image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:21.628493image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:23.763854image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:25.828425image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:28.071156image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:03.684182image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:05.910732image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:08.197568image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:10.459046image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:12.784652image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:15.156649image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:17.429510image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:19.648399image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:21.796713image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:23.936620image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:25.994995image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:28.237411image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:03.869290image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:06.092567image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:08.384391image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:10.645320image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:12.985406image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:15.345460image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:17.602932image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:19.826714image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:21.977313image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:24.103854image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:26.162202image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:28.403781image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:04.040651image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:06.277879image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:08.648063image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:10.811003image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:13.166408image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:15.525892image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:17.785388image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:20.075743image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:22.134469image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:24.270675image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:26.330907image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:28.572844image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:04.204378image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:06.461949image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:08.833625image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:10.992025image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:13.335488image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:15.708873image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:17.990981image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:20.243892image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:22.309976image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:24.440303image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:26.498502image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:28.737707image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:04.371058image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:06.644341image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:09.003221image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:11.177598image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:13.519037image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:15.870939image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:18.186839image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:20.416691image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:22.479791image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:24.591223image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-24T00:29:26.647266image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Correlations

2022-02-24T00:29:32.045146image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-02-24T00:29:32.222337image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-02-24T00:29:32.329274image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-02-24T00:29:32.438650image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-02-24T00:29:28.857004image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
A simple visualization of nullity by column.
2022-02-24T00:29:29.121704image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

df_indexIDugrizuErrgErrrErriErrzErr
00123764594290511076822.37392420.30102318.91428618.43199718.1595170.3126670.0532210.0514270.0557310.075440
11123764594290556977322.49706620.95227219.39496018.85327918.4348090.5427270.1155570.0791840.0797350.109295
22123764594397832838122.67897621.65057819.88625319.21400518.8393230.5290010.1530880.0885230.0882520.112267
33123764594397852481921.03238318.86598617.56185917.13313116.8293060.1795820.0404550.0490650.0590500.074079
44123764594397852488921.57626720.21681018.49581917.97449517.6144410.2571840.0676140.0560280.0632110.076636
55123764594397859051821.16587419.13066917.66862717.22780616.9494090.2679510.0553520.0592080.0700570.091337
66123764594397859076123.82711822.26603320.51006919.85076919.4928150.7256610.1998550.0989390.0937190.125562
77123764594397865605121.89442820.38026818.85330818.34680917.9446680.3507420.0760740.0613990.0661410.161078
88123764594397872150222.07780120.38406019.02260218.58708618.2957130.3426190.0654580.0581500.0650430.079621
99123764594397872154621.39077020.25034018.93605218.48809218.2062680.2449760.0732160.0657400.0726600.089991

Last rows

df_indexIDugrizuErrgErrrErriErrzErr
31919875915123768053081525578024.33683421.41881219.51132618.80689418.3568591.0484350.1143280.0785060.0889510.102196
31919975916123768053081571398123.45782721.23199819.37774318.68882918.2109780.9605360.1240570.0822710.0932210.116708
31920075917123768053081650074822.75956221.76936920.68083619.65621919.2881390.7859100.2172120.2110300.1819290.238482
31920175918123768053081663198123.90333222.32110820.87495019.79347219.2833941.1683630.2791900.2065760.1635260.209199
31920275919123768053081741839022.27361120.69907019.87421619.12998218.7572460.7197860.1322740.1749940.1866240.240496
31920375920123768053081748311725.54130021.28424119.37867418.57955918.1373000.9045650.2176600.1520720.1660660.193869
31920475921123768053081918741126.02027321.84404420.21909719.30853518.8929420.4811630.1998160.1420570.1390650.175742
31920575922123768053081925321422.18565923.07504721.33887520.10450619.5790480.2870640.3488830.2045750.1468780.196234
31920675923123768053135442025325.84915922.01780520.32897019.44092418.8436490.4127660.2210410.1470980.1408610.159505
31920775924123768053135632050121.98962421.69380820.04319019.10477318.5510730.3472560.1347240.1044780.1003720.123098